A Collaborative Project: Development of An Undergraduate Data Mining Course

合作项目:本科数据挖掘课程的开发

基本信息

  • 批准号:
    0231448
  • 负责人:
  • 金额:
    $ 5.27万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2003
  • 资助国家:
    美国
  • 起止时间:
    2003-01-01 至 2004-12-31
  • 项目状态:
    已结题

项目摘要

Data mining is an emerging field. The knowledge of data mining has been in demand in the IT industry and in new areas like bioinformatics, information assurance, and homeland security where data are massive. Traditionally, data mining courses are offered at the graduate level; now, this type of course is needed at the undergraduate level to increase interest in this area and address labor market demands. This collaborative project between Arizona and Wright State Universities develops an undergraduate data mining course for junior and seniors. The objectives are: develop a course that can be taught either by semester ASU or quarter WSU term, establish vehicles and approaches to increase student retention in the course, and promote data mining skills essential to problem solving. The objectives are accomplished in several ways: designing a pre-assessment instrument measuring student knowledge of data mining, and on-line tutorials; develop course materials that will enhance problem solving skills through reflection, critique, exercises, discerning theory from practice; and using a continuous evaluation process that addresses not only student achievement but also enrollment retention. Input from leading IT industry is used to incorporate immediate practical needs. The results of the project including evaluation are published via various means. Notes, supporting materials, projects, and exams are made available on the course web site.
数据挖掘是一个新兴的领域。数据挖掘的知识已经在IT行业和新的领域,如生物信息学,信息保障和国土安全的数据是巨大的需求。传统上,数据挖掘课程是在研究生阶段提供的;现在,本科阶段需要这种类型的课程,以提高对这一领域的兴趣并满足劳动力市场的需求。亚利桑那州和赖特州立大学之间的这个合作项目为大三和大四学生开发了一门本科数据挖掘课程。其目标是:开发一门课程,可以由学期ASU或季度WSU学期教授,建立车辆和方法,以增加学生在课程中的保留,并促进数据挖掘技能解决问题所必需的。这些目标是通过几种方式实现的:设计一个预评估工具来衡量学生的数据挖掘知识,以及在线教程;开发课程材料,通过反思,批判,练习,从实践中辨别理论,提高解决问题的能力;以及使用一个持续的评估过程,不仅解决学生的成绩,而且还解决入学保留问题。主要信息技术行业的投入被用来纳入即时的实际需要。该项目的结果,包括评估,通过各种方式公布。笔记、辅助材料、专题和考试都可以在课程网站上找到。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

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Huan Liu其他文献

Silica coating with well-defined micro-nano hierarchy for universal and stable surface superhydrophobicity
具有明确微纳米层次结构的二氧化硅涂层,具有通用且稳定的表面超疏水性
  • DOI:
    10.1016/j.cplett.2019.06.001
  • 发表时间:
    2019-09
  • 期刊:
  • 影响因子:
    2.8
  • 作者:
    Huan Liu;Wei Geng;Cheng-Jing Jin;Si-Ming Wu;Yi Lu;Jie Hu;Hao-Zheng Yu;Gang-Gang Chang;Tian Zhao;Ying Wan;Zhi-Qiang Luo;Ge Tian;Xiao-Yu Yang
  • 通讯作者:
    Xiao-Yu Yang
The Construction and Application of a Multipoint Sampling System for Vehicle Exhaust Plumes
汽车尾气多点采样系统的构建与应用
  • DOI:
    10.4209/aaqr.2017.02.0076
  • 发表时间:
    2017
  • 期刊:
  • 影响因子:
    4
  • 作者:
    Xianbao Shen;Zhiliang Yao;Kebin He;Xinyue Cao;Huan Liu
  • 通讯作者:
    Huan Liu
MnO2/HF/HNO3/H2O System for High-Performance Texturization on Multi-Crystalline Silicon
用于多晶硅高性能织构化的 MnO2/HF/HNO3/H2O 系统
  • DOI:
    10.4028/www.scientific.net/msf.960.263
  • 发表时间:
    2019-06
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Huan Liu;Lei Zhao;Hongwei Diao;Wenjing Wang
  • 通讯作者:
    Wenjing Wang
Effect of spatial distribution of boron and oxygen concentration on DNA damage induced from boron neutron capture therapy using Monte Carlo simulations
使用蒙特卡罗模拟,硼和氧浓度的空间分布对硼中子俘获疗法引起的 DNA 损伤的影响
  • DOI:
    10.1080/09553002.2021.1928785
  • 发表时间:
    2021-05
  • 期刊:
  • 影响因子:
    2.6
  • 作者:
    Jie Qi;Changran Geng;Xiaobin Tang;Feng Tian;Yang Han;Huan Liu;Yuanhao Liu;Silva Bortolussi;Fada Guan
  • 通讯作者:
    Fada Guan
Multiauthority Attribute-Based Keyword Search over Cloud-Edge-End Collaboration in IoV
车联网云边端协作基于多权限属性的关键词搜索

Huan Liu的其他文献

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{{ truncateString('Huan Liu', 18)}}的其他基金

SaTC: EDU: AI for Cybersecurity Education via an LLM-enabled Security Knowledge Graph
SaTC:EDU:通过支持 LLM 的安全知识图进行网络安全教育的人工智能
  • 批准号:
    2335666
  • 财政年份:
    2024
  • 资助金额:
    $ 5.27万
  • 项目类别:
    Standard Grant
III: SMALL: Graph Contrastive Learning for Few-Shot Node Classification
III:SMALL:少样本节点分类的图对比学习
  • 批准号:
    2229461
  • 财政年份:
    2023
  • 资助金额:
    $ 5.27万
  • 项目类别:
    Standard Grant
EAGER: SaTC-EDU: Artificial Intelligence for Cybersecurity Education via a Machine Learning-Enabled Security Knowledge Graph
EAGER:SaTC-EDU:通过机器学习支持的安全知识图进行网络安全教育的人工智能
  • 批准号:
    2114789
  • 财政年份:
    2021
  • 资助金额:
    $ 5.27万
  • 项目类别:
    Standard Grant
III: Small: Discovering and Characterizing Implicit Links in Graph Data
III:小:发现和表征图数据中的隐式链接
  • 批准号:
    1614576
  • 财政年份:
    2016
  • 资助金额:
    $ 5.27万
  • 项目类别:
    Standard Grant
III: Small: Transforming Feature Selection to Harness the Power of Social Media
III:小:转变特征选择以利用社交媒体的力量
  • 批准号:
    1217466
  • 财政年份:
    2012
  • 资助金额:
    $ 5.27万
  • 项目类别:
    Standard Grant
NSF Conference Sponsorship for the Third International Conference on Social Computing, Behavioral Modeling, and Prediction
NSF 会议赞助第三届社会计算、行为建模和预测国际会议
  • 批准号:
    1019597
  • 财政年份:
    2010
  • 资助金额:
    $ 5.27万
  • 项目类别:
    Standard Grant
NSF Workshop Sponsorship for the Second International Workshop on Social Computing, Behavioral Modeling, and Prediction
NSF 研讨会赞助第二届社会计算、行为建模和预测国际研讨会
  • 批准号:
    0908506
  • 财政年份:
    2009
  • 资助金额:
    $ 5.27万
  • 项目类别:
    Standard Grant
III-COR-Small: Beyond Feature Selection and Extraction - An Integrated Framework for High-Dimensional Data of Small Labeled Samples
III-COR-Small:超越特征选择和提取 - 小标记样本高维数据的集成框架
  • 批准号:
    0812551
  • 财政年份:
    2008
  • 资助金额:
    $ 5.27万
  • 项目类别:
    Continuing Grant
SGER: Toward a Unifying Taxonomy for Feature Selection
SGER:迈向特征选择的统一分类法
  • 批准号:
    0127815
  • 财政年份:
    2001
  • 资助金额:
    $ 5.27万
  • 项目类别:
    Standard Grant

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